class_docstr: Apply a `power transform <https://en.wikipedia.org/wiki/Power_transform>`_ to
  make your data more normally distributed.
  
  Some models expect data to be normally distributed. By making your data more
  Gaussian-like, you might be able to improve your model's performance.
  
  This preprocessor supports the following transformations:
  
  * `Yeo-Johnson <https://en.wikipedia.org/wiki/Power_transform#Yeo%E2%80%93Johnson_transformation>`_
  * `Box-Cox <https://en.wikipedia.org/wiki/Power_transform#Box%E2%80%93Cox_transformation>`_
  
  Box-Cox requires all data to be positive.
  
  .. warning::
  
      You need to manually specify the transform's power parameter. If you
      choose a bad value, the transformation might not work well.
  
  Args:
      columns: The columns to separately transform.
      power: A parameter that determines how your data is transformed. Practioners
          typically set ``power`` between :math:`-2.5` and :math:`2.5`, although you
          may need to try different values to find one that works well.
      method: A string representing which transformation to apply. Supports
          ``"yeo-johnson"`` and ``"box-cox"``. If you choose ``"box-cox"``, your data
          needs to be positive. Defaults to ``"yeo-johnson"``.
code: def __init__(
      self,
      columns: List[str],
      power: float,
      method: str = "yeo-johnson",
  ):
      self.columns = columns
      self.method = method
      self.power = power
  
      if method not in self._valid_methods:
          raise ValueError(
              f"Method {method} is not supported."
              f"Supported values are: {self._valid_methods}"
          )
  
file_path: ray/python/ray/data/preprocessors/transformer.py
imports: from typing import List
  import numpy
  import pandas
  from ray.data.preprocessor import Preprocessor
  from ray.util.annotations import PublicAPI
label_desc: Use image node_id 1 to create a new PowerTransformer object from inherited base classes: Preprocessor with example: obj = PowerTransformer(columns, power, method)